Overview

Dataset statistics

Number of variables55
Number of observations2467
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.0 MiB
Average record size in memory440.1 B

Variable types

BOOL47
NUM7
CAT1

Warnings

packages_running_com.android.providers.contacts is highly correlated with packages_running_com.android.providers.applications and 1 other fieldsHigh correlation
packages_running_com.android.providers.applications is highly correlated with packages_running_com.android.providers.contacts and 1 other fieldsHigh correlation
packages_running_com.android.providers.drm is highly correlated with packages_running_com.android.providers.downloads and 1 other fieldsHigh correlation
packages_running_com.android.providers.downloads is highly correlated with packages_running_com.android.providers.drm and 1 other fieldsHigh correlation
packages_running_com.android.providers.media is highly correlated with packages_running_com.android.providers.downloads and 1 other fieldsHigh correlation
packages_running_com.android.providers.userdictionary is highly correlated with packages_running_com.android.providers.applications and 1 other fieldsHigh correlation
packages_running_com.google.android.apps.genie.geniewidget is highly correlated with packages_running_ch.smalltech.battery.freeHigh correlation
packages_running_ch.smalltech.battery.free is highly correlated with packages_running_com.google.android.apps.genie.geniewidgetHigh correlation
year is highly correlated with month and 1 other fieldsHigh correlation
month is highly correlated with yearHigh correlation
packages_running_com.tf.thinkdroid.sg is highly correlated with yearHigh correlation
df_index has unique values Unique
battery_level has 1303 (52.8%) zeros Zeros
battery_plugged has 2342 (94.9%) zeros Zeros
battery_status has 1394 (56.5%) zeros Zeros
slot has 57 (2.3%) zeros Zeros

Reproduction

Analysis started2020-12-05 15:39:59.728425
Analysis finished2020-12-05 15:40:13.463145
Duration13.73 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

df_index
Real number (ℝ≥0)

UNIQUE

Distinct2467
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1233.408593
Minimum0
Maximum2468
Zeros1
Zeros (%)< 0.1%
Memory size19.3 KiB
2020-12-05T16:40:13.509769image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile123.3
Q1616.5
median1233
Q31850.5
95-th percentile2343.7
Maximum2468
Range2468
Interquartile range (IQR)1234

Descriptive statistics

Standard deviation712.757454
Coefficient of variation (CV)0.5778761862
Kurtosis-1.200256465
Mean1233.408593
Median Absolute Deviation (MAD)617
Skewness0.0006560782213
Sum3042819
Variance508023.1882
MonotocityStrictly increasing
2020-12-05T16:40:13.617897image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
20471< 0.1%
 
12201< 0.1%
 
12341< 0.1%
 
12321< 0.1%
 
12301< 0.1%
 
12281< 0.1%
 
12261< 0.1%
 
12241< 0.1%
 
12221< 0.1%
 
12181< 0.1%
 
Other values (2457)245799.6%
 
ValueCountFrequency (%) 
01< 0.1%
 
11< 0.1%
 
21< 0.1%
 
31< 0.1%
 
41< 0.1%
 
ValueCountFrequency (%) 
24681< 0.1%
 
24671< 0.1%
 
24661< 0.1%
 
24651< 0.1%
 
24641< 0.1%
 

battery_level
Real number (ℝ)

ZEROS

Distinct41
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1495743818
Minimum-10
Maximum30
Zeros1303
Zeros (%)52.8%
Memory size19.3 KiB
2020-12-05T16:40:13.725529image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-10
5-th percentile-3
Q1-1
median0
Q30
95-th percentile2
Maximum30
Range40
Interquartile range (IQR)1

Descriptive statistics

Standard deviation4.235839778
Coefficient of variation (CV)28.31928654
Kurtosis23.94171408
Mean0.1495743818
Median Absolute Deviation (MAD)0
Skewness4.670915429
Sum369
Variance17.94233863
MonotocityNot monotonic
2020-12-05T16:40:13.828696image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%) 
0130352.8%
 
-173729.9%
 
-21486.0%
 
-3602.4%
 
-4471.9%
 
-5200.8%
 
11100.4%
 
290.4%
 
180.3%
 
2480.3%
 
Other values (31)1174.7%
 
ValueCountFrequency (%) 
-101< 0.1%
 
-930.1%
 
-820.1%
 
-730.1%
 
-680.3%
 
ValueCountFrequency (%) 
301< 0.1%
 
2940.2%
 
2840.2%
 
2750.2%
 
2640.2%
 

battery_plugged
Real number (ℝ≥0)

ZEROS

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.05164842589
Minimum0
Maximum2
Zeros2342
Zeros (%)94.9%
Memory size19.3 KiB
2020-12-05T16:40:13.926408image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.5
Maximum2
Range2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2343444154
Coefficient of variation (CV)4.537300244
Kurtosis25.71638198
Mean0.05164842589
Median Absolute Deviation (MAD)0
Skewness4.884630798
Sum127.4166667
Variance0.05491730502
MonotocityNot monotonic
2020-12-05T16:40:14.001304image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
0234294.9%
 
11024.1%
 
0.5120.5%
 
290.4%
 
0.66666666671< 0.1%
 
0.751< 0.1%
 
ValueCountFrequency (%) 
0234294.9%
 
0.5120.5%
 
0.66666666671< 0.1%
 
0.751< 0.1%
 
11024.1%
 
ValueCountFrequency (%) 
290.4%
 
11024.1%
 
0.751< 0.1%
 
0.66666666671< 0.1%
 
0.5120.5%
 

battery_status
Real number (ℝ≥0)

ZEROS

Distinct12
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3494798
Minimum0
Maximum5
Zeros1394
Zeros (%)56.5%
Memory size19.3 KiB
2020-12-05T16:40:14.083640image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile3
Maximum5
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.582000072
Coefficient of variation (CV)1.172303633
Kurtosis-1.379126317
Mean1.3494798
Median Absolute Deviation (MAD)0
Skewness0.4673774298
Sum3329.166667
Variance2.502724227
MonotocityNot monotonic
2020-12-05T16:40:14.253272image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%) 
0139456.5%
 
393237.8%
 
5702.8%
 
2411.7%
 
2.590.4%
 
460.2%
 
4.550.2%
 
2.33333333330.1%
 
3.530.1%
 
3.66666666720.1%
 
Other values (2)20.1%
 
ValueCountFrequency (%) 
0139456.5%
 
2411.7%
 
2.33333333330.1%
 
2.590.4%
 
2.6666666671< 0.1%
 
ValueCountFrequency (%) 
5702.8%
 
4.6666666671< 0.1%
 
4.550.2%
 
460.2%
 
3.66666666720.1%
 

day
Real number (ℝ≥0)

Distinct31
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.5804621
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Memory size19.3 KiB
2020-12-05T16:40:14.344040image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q15
median13
Q321
95-th percentile30
Maximum31
Range30
Interquartile range (IQR)16

Descriptive statistics

Standard deviation9.297131264
Coefficient of variation (CV)0.6845960908
Kurtosis-1.032164564
Mean13.5804621
Median Absolute Deviation (MAD)8
Skewness0.4290798367
Sum33503
Variance86.43664975
MonotocityNot monotonic
2020-12-05T16:40:14.435303image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%) 
21445.8%
 
11345.4%
 
41335.4%
 
141245.0%
 
161184.8%
 
31164.7%
 
131114.5%
 
71114.5%
 
81074.3%
 
291044.2%
 
Other values (21)126551.3%
 
ValueCountFrequency (%) 
11345.4%
 
21445.8%
 
31164.7%
 
41335.4%
 
51004.1%
 
ValueCountFrequency (%) 
31642.6%
 
30933.8%
 
291044.2%
 
28923.7%
 
27522.1%
 

month
Real number (ℝ≥0)

HIGH CORRELATION

Distinct8
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.771787596
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Memory size19.3 KiB
2020-12-05T16:40:14.527560image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q310
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)9

Descriptive statistics

Standard deviation4.459992309
Coefficient of variation (CV)0.7727228756
Kurtosis-1.779821852
Mean5.771787596
Median Absolute Deviation (MAD)2
Skewness0.1551145686
Sum14239
Variance19.89153139
MonotocityNot monotonic
2020-12-05T16:40:14.599975image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
168227.6%
 
244618.1%
 
943317.6%
 
1233713.7%
 
1025710.4%
 
31506.1%
 
111365.5%
 
8261.1%
 
ValueCountFrequency (%) 
168227.6%
 
244618.1%
 
31506.1%
 
8261.1%
 
943317.6%
 
ValueCountFrequency (%) 
1233713.7%
 
111365.5%
 
1025710.4%
 
943317.6%
 
8261.1%
 
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
1
1723 
0
744 
ValueCountFrequency (%) 
1172369.8%
 
074430.2%
 
2020-12-05T16:40:14.658504image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
0
2439 
1
 
28
ValueCountFrequency (%) 
0243998.9%
 
1281.1%
 
2020-12-05T16:40:14.695207image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
0
2459 
1
 
8
ValueCountFrequency (%) 
0245999.7%
 
180.3%
 
2020-12-05T16:40:14.730919image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
0
2213 
1
254 
ValueCountFrequency (%) 
0221389.7%
 
125410.3%
 
2020-12-05T16:40:14.767127image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
0
1361 
1
1106 
ValueCountFrequency (%) 
0136155.2%
 
1110644.8%
 
2020-12-05T16:40:14.803831image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
1
1342 
0
1125 
ValueCountFrequency (%) 
1134254.4%
 
0112545.6%
 
2020-12-05T16:40:14.840039image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
0
2443 
1
 
24
ValueCountFrequency (%) 
0244399.0%
 
1241.0%
 
2020-12-05T16:40:14.876247image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
0
1252 
1
1215 
ValueCountFrequency (%) 
0125250.7%
 
1121549.3%
 
2020-12-05T16:40:14.912951image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
0
2227 
1
240 
ValueCountFrequency (%) 
0222790.3%
 
12409.7%
 
2020-12-05T16:40:14.949159image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
0
2466 
1
 
1
ValueCountFrequency (%) 
02466> 99.9%
 
11< 0.1%
 
2020-12-05T16:40:14.985863image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
1
2460 
0
 
7
ValueCountFrequency (%) 
1246099.7%
 
070.3%
 
2020-12-05T16:40:15.021575image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
1
1846 
0
621 
ValueCountFrequency (%) 
1184674.8%
 
062125.2%
 
2020-12-05T16:40:15.057783image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
1
2460 
0
 
7
ValueCountFrequency (%) 
1246099.7%
 
070.3%
 
2020-12-05T16:40:15.093991image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
1
2458 
0
 
9
ValueCountFrequency (%) 
1245899.6%
 
090.4%
 
2020-12-05T16:40:15.129703image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
1
2458 
0
 
9
ValueCountFrequency (%) 
1245899.6%
 
090.4%
 
2020-12-05T16:40:15.165911image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
1
2458 
0
 
9
ValueCountFrequency (%) 
1245899.6%
 
090.4%
 
2020-12-05T16:40:15.202119image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
1
2460 
0
 
7
ValueCountFrequency (%) 
1246099.7%
 
070.3%
 
2020-12-05T16:40:15.238823image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
0
1933 
1
534 
ValueCountFrequency (%) 
0193378.4%
 
153421.6%
 
2020-12-05T16:40:15.275031image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
1
1683 
0
784 
ValueCountFrequency (%) 
1168368.2%
 
078431.8%
 
2020-12-05T16:40:15.311239image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
1
2421 
0
 
46
ValueCountFrequency (%) 
1242198.1%
 
0461.9%
 
2020-12-05T16:40:15.347447image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
1
1684 
0
783 
ValueCountFrequency (%) 
1168468.3%
 
078331.7%
 
2020-12-05T16:40:15.384151image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
1
1662 
0
805 
ValueCountFrequency (%) 
1166267.4%
 
080532.6%
 
2020-12-05T16:40:15.420358image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
1
1533 
0
934 
ValueCountFrequency (%) 
1153362.1%
 
093437.9%
 
2020-12-05T16:40:15.456567image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
1
1363 
0
1104 
ValueCountFrequency (%) 
1136355.2%
 
0110444.8%
 
2020-12-05T16:40:15.493270image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
1
1807 
0
660 
ValueCountFrequency (%) 
1180773.2%
 
066026.8%
 
2020-12-05T16:40:15.529478image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
0
1379 
1
1088 
ValueCountFrequency (%) 
0137955.9%
 
1108844.1%
 
2020-12-05T16:40:15.566182image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
1
2461 
0
 
6
ValueCountFrequency (%) 
1246199.8%
 
060.2%
 
2020-12-05T16:40:15.602390image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
0
1806 
1
661 
ValueCountFrequency (%) 
0180673.2%
 
166126.8%
 
2020-12-05T16:40:15.638102image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
1
1789 
0
678 
ValueCountFrequency (%) 
1178972.5%
 
067827.5%
 
2020-12-05T16:40:15.674310image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
0
2406 
1
 
61
ValueCountFrequency (%) 
0240697.5%
 
1612.5%
 
2020-12-05T16:40:15.711014image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
0
2344 
1
 
123
ValueCountFrequency (%) 
0234495.0%
 
11235.0%
 
2020-12-05T16:40:15.746726image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
0
1683 
1
784 
ValueCountFrequency (%) 
0168368.2%
 
178431.8%
 
2020-12-05T16:40:15.783430image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
1
2418 
0
 
49
ValueCountFrequency (%) 
1241898.0%
 
0492.0%
 
2020-12-05T16:40:15.819638image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
1
1845 
0
622 
ValueCountFrequency (%) 
1184574.8%
 
062225.2%
 
2020-12-05T16:40:15.855350image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
1
2290 
0
 
177
ValueCountFrequency (%) 
1229092.8%
 
01777.2%
 
2020-12-05T16:40:15.892054image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
0
1972 
1
495 
ValueCountFrequency (%) 
0197279.9%
 
149520.1%
 
2020-12-05T16:40:15.928262image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
0
2007 
1
460 
ValueCountFrequency (%) 
0200781.4%
 
146018.6%
 
2020-12-05T16:40:15.964470image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
0
2393 
1
 
74
ValueCountFrequency (%) 
0239397.0%
 
1743.0%
 
2020-12-05T16:40:16.000678image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
1
1310 
0
1157 
ValueCountFrequency (%) 
1131053.1%
 
0115746.9%
 
2020-12-05T16:40:16.036390image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
0
1389 
1
1078 
ValueCountFrequency (%) 
0138956.3%
 
1107843.7%
 
2020-12-05T16:40:16.073094image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
0
2422 
1
 
45
ValueCountFrequency (%) 
0242298.2%
 
1451.8%
 
2020-12-05T16:40:16.109798image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
0
2401 
1
 
66
ValueCountFrequency (%) 
0240197.3%
 
1662.7%
 
2020-12-05T16:40:16.145509image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
0
1301 
1
1166 
ValueCountFrequency (%) 
0130152.7%
 
1116647.3%
 
2020-12-05T16:40:16.291333image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
1
1373 
0
1094 
ValueCountFrequency (%) 
1137355.7%
 
0109444.3%
 
2020-12-05T16:40:16.327541image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
1
2463 
0
 
4
ValueCountFrequency (%) 
1246399.8%
 
040.2%
 
2020-12-05T16:40:16.364245image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
0
2466 
1
 
1
ValueCountFrequency (%) 
02466> 99.9%
 
11< 0.1%
 
2020-12-05T16:40:16.400453image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
0
2466 
1
 
1
ValueCountFrequency (%) 
02466> 99.9%
 
11< 0.1%
 
2020-12-05T16:40:16.436661image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

slot
Real number (ℝ≥0)

ZEROS

Distinct48
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.73530604
Minimum0
Maximum47
Zeros57
Zeros (%)2.3%
Memory size19.3 KiB
2020-12-05T16:40:16.505605image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q112
median24
Q336
95-th percentile45
Maximum47
Range47
Interquartile range (IQR)24

Descriptive statistics

Standard deviation13.89810788
Coefficient of variation (CV)0.5855457627
Kurtosis-1.183658581
Mean23.73530604
Median Absolute Deviation (MAD)12
Skewness-0.05090949561
Sum58555
Variance193.1574026
MonotocityNot monotonic
2020-12-05T16:40:16.609765image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%) 
3622.5%
 
23612.5%
 
31612.5%
 
27602.4%
 
1602.4%
 
21572.3%
 
26572.3%
 
0572.3%
 
39562.3%
 
32562.3%
 
Other values (38)188076.2%
 
ValueCountFrequency (%) 
0572.3%
 
1602.4%
 
2411.7%
 
3622.5%
 
4562.3%
 
ValueCountFrequency (%) 
47552.2%
 
46512.1%
 
45471.9%
 
44562.3%
 
43562.3%
 

year
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
2013
1278 
2012
1189 
ValueCountFrequency (%) 
2013127851.8%
 
2012118948.2%
 
2020-12-05T16:40:16.707973image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-05T16:40:16.763029image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:16.825525image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length6
Mean length6
Min length6

Interactions

2020-12-05T16:40:01.778391image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:01.876599image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:01.982247image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:02.088390image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:02.184118image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:02.280838image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:02.381030image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:02.471302image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:02.575958image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:02.688549image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:02.803125image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:02.907285image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:03.012933image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:03.116101image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:03.217781image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:03.323429image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:03.438501image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:03.554565image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:03.660212image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:03.768340image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:03.872996image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:03.975172image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:04.067429image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:04.167124image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:04.269300image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:04.360564image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:04.453811image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:04.544579image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:04.631875image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:04.726611image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:04.829283image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:04.933443image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:05.027683image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:05.123411image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:05.503842image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:05.595602image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:05.686866image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:05.794498image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:05.899154image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:05.988930image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:06.081187image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:06.171458image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:06.261233image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:06.351009image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:06.449217image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:06.548417image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:06.637697image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:06.728961image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:06.817249image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Correlations

2020-12-05T16:40:16.968868image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-12-05T16:40:19.049091image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-12-05T16:40:21.157088image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-12-05T16:40:23.282445image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2020-12-05T16:40:07.102448image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-05T16:40:11.996475image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Sample

First rows

df_indexbattery_levelbattery_pluggedbattery_statusdaymonthpackages_running_ch.smalltech.battery.freepackages_running_com.android.bluetoothpackages_running_com.android.calculator2packages_running_com.android.chromepackages_running_com.android.contactspackages_running_com.android.defcontainerpackages_running_com.android.keychainpackages_running_com.android.mmspackages_running_com.android.musicfxpackages_running_com.android.packageinstallerpackages_running_com.android.providers.applicationspackages_running_com.android.providers.calendarpackages_running_com.android.providers.contactspackages_running_com.android.providers.downloadspackages_running_com.android.providers.drmpackages_running_com.android.providers.mediapackages_running_com.android.providers.userdictionarypackages_running_com.android.settingspackages_running_com.android.vendingpackages_running_com.google.android.apps.bookspackages_running_com.google.android.apps.genie.geniewidgetpackages_running_com.google.android.apps.pluspackages_running_com.google.android.apps.uploaderpackages_running_com.google.android.browserpackages_running_com.google.android.calendarpackages_running_com.google.android.deskclockpackages_running_com.google.android.emailpackages_running_com.google.android.exchangepackages_running_com.google.android.gallery3dpackages_running_com.google.android.gmpackages_running_com.google.android.gmspackages_running_com.google.android.googlequicksearchboxpackages_running_com.google.android.gsf.loginpackages_running_com.google.android.inputmethod.latin.dictionarypackpackages_running_com.google.android.locationpackages_running_com.google.android.musicpackages_running_com.google.android.partnersetuppackages_running_com.google.android.setupwizardpackages_running_com.google.android.youtubepackages_running_com.googlecode.pythonforandroidpackages_running_com.halfbrick.fruitninjafreepackages_running_com.rovio.angrybirdsspace.adspackages_running_com.tf.thinkdroid.sgpackages_running_de.kicktipp.mbookmarkpackages_running_edu.udo.cs.ess.mobidac.targetpackages_running_org.openintents.filemanagerpackages_running_stream.androidslotyear
0025.01.02.031.08.00.00.00.01.00.00.00.00.00.00.01.01.01.01.01.01.01.00.01.00.00.01.01.00.01.01.01.01.01.00.00.00.01.00.01.01.00.00.01.00.00.00.00.00.01.00.00.03.02012.0
113.00.00.031.08.00.00.00.01.00.00.00.00.00.00.01.01.01.01.01.01.01.00.01.00.00.01.01.00.01.01.01.01.01.00.00.00.01.00.01.01.00.00.01.00.00.00.00.00.01.00.00.04.02012.0
221.01.04.531.08.00.00.00.01.00.00.00.00.00.00.01.01.01.01.01.01.01.00.01.00.00.01.01.00.01.01.01.01.01.00.00.00.01.00.01.01.00.00.01.01.00.00.00.00.01.00.00.08.02012.0
330.01.05.031.08.00.00.00.01.00.00.00.00.00.00.01.01.01.01.01.01.01.00.01.00.00.01.01.00.01.01.01.01.01.00.00.00.01.00.01.01.00.00.01.01.00.00.00.00.01.00.00.012.02012.0
440.00.54.031.08.00.00.00.00.00.00.00.00.00.00.01.01.01.01.01.01.01.00.01.00.00.01.01.00.00.01.01.01.01.00.00.00.01.00.01.01.00.00.00.01.00.00.00.00.01.00.00.016.02012.0
550.00.00.031.08.00.00.00.00.00.00.00.00.00.00.01.00.01.01.01.01.01.00.01.00.00.01.01.00.00.01.01.01.01.00.00.00.01.00.01.01.00.00.01.01.00.00.00.00.01.00.00.017.02012.0
66-2.00.00.031.08.00.00.00.00.00.00.00.00.00.00.01.00.01.01.01.01.01.00.00.00.00.01.01.00.00.01.01.01.01.00.00.00.01.00.01.01.00.00.01.01.00.00.00.00.01.00.00.018.02012.0
77-3.00.03.031.08.00.00.00.00.00.00.00.00.00.00.01.00.01.01.01.01.01.00.00.00.00.01.01.00.00.01.01.01.01.00.00.00.01.00.01.01.00.00.01.01.00.00.00.00.01.00.00.019.02012.0
88-3.00.00.031.08.00.00.00.00.00.00.00.00.00.00.01.00.01.01.01.01.01.00.00.00.00.01.01.00.00.01.01.01.01.00.00.00.01.00.01.01.00.00.01.01.00.00.00.00.01.00.00.021.02012.0
99-3.00.00.031.08.00.00.00.00.00.00.00.00.00.00.01.00.01.01.01.01.01.00.00.00.00.01.01.00.00.01.01.01.01.00.00.00.01.00.01.01.00.00.01.01.00.00.00.00.01.00.00.022.02012.0

Last rows

df_indexbattery_levelbattery_pluggedbattery_statusdaymonthpackages_running_ch.smalltech.battery.freepackages_running_com.android.bluetoothpackages_running_com.android.calculator2packages_running_com.android.chromepackages_running_com.android.contactspackages_running_com.android.defcontainerpackages_running_com.android.keychainpackages_running_com.android.mmspackages_running_com.android.musicfxpackages_running_com.android.packageinstallerpackages_running_com.android.providers.applicationspackages_running_com.android.providers.calendarpackages_running_com.android.providers.contactspackages_running_com.android.providers.downloadspackages_running_com.android.providers.drmpackages_running_com.android.providers.mediapackages_running_com.android.providers.userdictionarypackages_running_com.android.settingspackages_running_com.android.vendingpackages_running_com.google.android.apps.bookspackages_running_com.google.android.apps.genie.geniewidgetpackages_running_com.google.android.apps.pluspackages_running_com.google.android.apps.uploaderpackages_running_com.google.android.browserpackages_running_com.google.android.calendarpackages_running_com.google.android.deskclockpackages_running_com.google.android.emailpackages_running_com.google.android.exchangepackages_running_com.google.android.gallery3dpackages_running_com.google.android.gmpackages_running_com.google.android.gmspackages_running_com.google.android.googlequicksearchboxpackages_running_com.google.android.gsf.loginpackages_running_com.google.android.inputmethod.latin.dictionarypackpackages_running_com.google.android.locationpackages_running_com.google.android.musicpackages_running_com.google.android.partnersetuppackages_running_com.google.android.setupwizardpackages_running_com.google.android.youtubepackages_running_com.googlecode.pythonforandroidpackages_running_com.halfbrick.fruitninjafreepackages_running_com.rovio.angrybirdsspace.adspackages_running_com.tf.thinkdroid.sgpackages_running_de.kicktipp.mbookmarkpackages_running_edu.udo.cs.ess.mobidac.targetpackages_running_org.openintents.filemanagerpackages_running_stream.androidslotyear
24572459-1.00.00.07.03.01.00.00.00.00.00.00.01.00.00.01.00.01.01.01.01.01.00.01.01.01.01.01.00.00.00.01.00.01.00.01.00.01.00.00.00.00.00.01.00.00.00.01.01.01.00.00.026.02013.0
24582460-1.00.00.07.03.01.00.00.00.00.00.00.01.00.00.01.00.01.01.01.01.01.00.01.01.01.01.01.00.00.00.01.00.01.00.01.00.01.00.00.00.00.00.01.00.00.00.01.01.01.00.00.027.02013.0
245924610.00.03.07.03.01.00.00.00.00.00.00.01.00.00.01.00.01.01.01.01.01.00.01.01.01.01.01.00.00.00.01.00.01.00.01.00.01.00.00.00.00.00.01.00.00.00.01.01.01.00.00.028.02013.0
246024620.00.00.07.03.01.00.00.00.00.00.00.01.00.00.01.00.01.01.01.01.01.00.01.01.01.01.01.00.00.00.01.00.01.00.01.00.01.00.00.00.00.00.01.00.00.00.01.01.01.00.00.029.02013.0
246124630.00.00.07.03.01.00.00.00.00.00.00.01.00.00.01.00.01.01.01.01.01.00.01.01.01.01.01.00.00.00.01.00.01.00.01.00.01.00.00.00.00.00.01.00.00.00.01.01.01.00.00.030.02013.0
246224640.00.00.07.03.01.00.00.00.00.00.00.01.00.00.01.00.01.01.01.01.01.00.01.01.01.01.01.00.00.00.01.00.01.00.01.00.01.00.00.00.00.00.01.00.00.00.01.01.01.00.00.031.02013.0
24632465-1.00.03.07.03.01.00.00.00.00.00.00.01.00.00.01.00.01.01.01.01.01.00.01.01.01.01.01.00.00.00.01.00.01.00.01.00.01.00.00.00.00.00.01.00.00.00.01.01.01.00.00.032.02013.0
24642466-1.00.03.07.03.01.00.00.00.00.00.00.01.00.00.01.00.01.01.01.01.01.00.01.01.01.01.01.00.00.00.01.00.01.00.01.00.01.00.00.00.00.00.01.00.00.00.01.01.01.00.00.036.02013.0
246524670.00.00.07.03.01.00.00.00.00.00.00.01.00.00.01.00.01.01.01.01.01.00.00.01.01.01.01.00.00.00.01.00.01.00.01.00.01.00.00.00.00.00.01.00.00.00.01.01.01.00.00.038.02013.0
246624680.00.00.07.03.01.00.00.00.00.00.00.01.00.00.01.00.01.01.01.01.01.00.00.01.01.01.01.00.00.00.01.00.01.00.01.00.01.00.00.00.00.00.01.00.00.00.01.01.01.00.00.039.02013.0